EVA: Complementary Modules 2019-20

Complementary modules organized by all institutions participating in the MSE.

Please note:

  • The number of inscriptions is typically restricted
  • Please consider the status field: only modules with "registration open" status can be booked
  • Module inscriptions have to be made via your advisor to the contact person as specified in the offering
Title: Human Interface Technology (HIT 2)
Short Code: EVA_BFH_MTE7105
ECTS Credits: 3
Organizer Details: MRU Technology in Sports und Medicine (TSM)

Oral exams at the end of the semester.

Decision Date: 1 February 2020 
Start Date: 18 February 2020 
End Date: 30 June 2020 
Date Details:

Spring semester, more or less every 2nd/3rd on a Friday (full-day), room HG 4.33 (Biel)


Full day course at 6 Fridays per semester.


English by default, but deviations according to the wishes of the students.

Description (max. 300 characters):

The HIT2 course consist of the 3 blocs distributed on 6 full day course days. The subjects of the modules are „Virtual Prototyping using SystemC“, „Image Analysis“ and „GPU Programming“.

Contents and Learning Objectives:

Virtual Prototyping Using SystemC(Prof. Dr. Torsten Maehne)

This course block introduces virtual prototyping of embedded systems using SystemC. Different models of computations are presented, which are needed to efficiently model and simulate today's complex and heterogeneous hardware/software systems and their interaction with the environment at different levels of abstraction (Register Transfer Level (RTL), Bit Cycle Accurate (BCA), Transaction Level (TL)). Based on hands-on exercises, modeling and debug strategies as well as design and verification methodologies for hardware/software co-design will be discussed.

Image Analysis(Prof. Marcus Hudritsch)

This course block gives a broader insight into digital image analysis. After a short wrap-up over image processing, we start with the classic feature engineering approach where the software engineer first segments an image into desired regions and represents them in processable data structures. After that, we learn different methods to extract meaningful and discriminative features that we can use in the final step to classify the image. The course block closes with machine learning for image analysis where we learn how to use unsupervised and supervise learning with large labeled datasets to classify images.



GPU Programming (Prof. Urs Künzler)

This course provides an introduction into modern GPU programming using the OpenGL GLSL Shading Language. We thereby get to know the basic principles of computer graphics. In particular we look at the working of the graphics rendering pipeline and its processing steps like vertex and geometry shader, hidden surface removal, rasterization, fragment processing and depth buffering. Several demo applications and small programming exercises will provide the participants a hands-on knowledge of tools and the GLSL language. The course evaluation will be based on a small, student defined and implemented project and its short presentation.

Admission: Elektro-Ing, Masch-Ing, Micro-Ing oder Informatik-Ing.
50% theory, 50% labs.   

Prof. Dr. M. Jacomet, marcel.jacomet@bfh.ch, 032 3216241

Contact Person E-Mail: marcel.jacomet@bfh.ch
Status: registration open
Specialization: Energy and Environment (EE)

Industrial Technologies (InT)

Information and Communication Technologies (ICT)


[Responsible for this text: Marcel Jacomet]